Abstract
Because of the development of the ageing population, most countries are facing an increasingly serious pension resources problem. With the development of Internet of Things, the integration of smart home and smart retirement provides a new solution for the new smart home for the elderly, to achieve the elderly to intelligently support the elderly. This paper is based on the development of this background, mainly to solve the problem of indoor activity recognition of the elderly, so as to prepare for the construction of smart medical care. The specific research process is to process the sensor data collected from the smart environment, identify different activities using RNN, LSTM and GRU models with strong ability to process time series data, realize the target of activity recognition.
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Zhao, Y., Li, Q., Farha, F., Zhu, T., Chen, L., Ning, H. (2019). Indoor Activity Recognition by Using Recurrent Neural Networks. In: Ning, H. (eds) Cyberspace Data and Intelligence, and Cyber-Living, Syndrome, and Health. CyberDI CyberLife 2019 2019. Communications in Computer and Information Science, vol 1138. Springer, Singapore. https://doi.org/10.1007/978-981-15-1925-3_15
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DOI: https://doi.org/10.1007/978-981-15-1925-3_15
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